Mashvisor MCP. Compare Airbnb vs Long-Term Rental ROI in seconds.

This server connects Mashvisor's full real estate analytics suite directly to your agent. You can run deep investment models against any potential property, pitting short-term Airbnb income right up against traditional long-term leases.

You don't just get a price; you get the whole market context—including historical performance trends over years. The tools let you sift through data and compare how different types of properties perform in the same area. You can find investment opportunities quickly by using search_properties and list_properties, filtering results across city, state, price range, and bedroom count to narrow down exactly what you need.

To get a broad view of an entire metro area, run get_city_listings. This pulls market listings filtered by attributes like historical price changes and days on market. For a deeper dive into the specifics of a single asset, use get_property to retrieve its core details, or pull granular data points for verification using get_airbnb_property.

When you're ready to crunch numbers, the server handles all the financial heavy lifting. You run get_investment_analysis on any property; it calculates key metrics like cap rates and cash-on-cash returns for both short-term and long-term strategies. To look at past performance—which is crucial for predicting seasonality and sustained revenue patterns—you use get_historical_performance.

This analyzes deep, past Airbnb data to give you a better idea of what's coming.

For local comparisons, the server gives you two ways to view neighborhood potential. You can run list_neighborhoods to compare investment metrics across several areas within one city market, or use get_airbnb_listings for current performance metrics and associated data in a specific target zone. If you're looking at standard income streams, get_rental_rates estimates typical long-term rental rates for properties ranging from 1 to 5 bedrooms using local rent distribution stats.

When you need to focus only on Airbnb potential, get_airbnb_listings pulls current listings and their associated performance metrics. You can also pull specific data for an existing listing with get_airbnb_property to view key metrics like occupancy rates, average daily rate (ADR), and projected monthly revenue. The entire system lets you compare the two major paths: high-yield short-term rentals versus stable long-term leases.

You don't have to manually check every corner of a city; list_properties handles filtering the database by location, bedroom count, and type, returning listings that already include both Airbnb and LTR metrics. You can also get a general sense of what’s available using get_city_listings, which pulls market-wide data points like price history and days on market across the city.

This entire stack means your agent executes complex commands—like asking to compare 3-bedroom properties in Manhattan vs. Brooklyn, calculating potential cash returns for both STR and LTR for each one, and checking historical occupancy rates for all of them. The server processes all that information and sends back structured data ready for your AI client to read and summarize.